Proteolytic processing, where biologically inactive precursor proteins are activated by specific cleavage of the polypeptide chain, is a common postranslational modification that is critical in diverse biological processes. Despite its importance, progress in proteomic analysis of proteolytic processing has lagged behind similar analyses of other posttranslational modifications. To address this shortcoming, a novel, high- throughput method for detecting products of proteolytic processing has recently been developed by the Wells lab. This method makes use of subtiligase, an engineered enzyme capable of ligating activated peptide substrates onto the N-termini of proteins. This unique enzyme makes it possible to detect the chemical byproduct of regulated proteolysis, a free N-terminal amino group, selectively over similarly reactive amines in lysine side chains and numerous other biomolecules. By using substrate peptides labeled with an affinity tag like biotin, it is possible to isolate only those proteins with free N-termini from a cell extract. These proteins can then be digested and identified by mass spectrometry. By also labeling with an isotope tag, it is possible to quantitatively compare the abundances of putative substrates in control and experimental extracts, cells, or tissues. Here we propose to expand the scope of this technique to encompass a number of medically relevant extracellular protease cascades. This proposal contains two independent but closely related goals: to improve the performance of the subtiligase enzyme in detecting diverse protease substrates, and to apply the original and improved enzymes to investigations of the complement cascade and the Alzheimer's disease beta-secretase BACE1. These model systems were chosen both for their medical importance and because they are good test systems to optimize this method. Complement is an intensely-studied and well- understood process that can be used to calibrate the quantitative power of the method. The biological role of BACE1, in contrast, is not well understood, and it provides an excellent system in which to hunt for unknown protease substrates. Relevance: This work will lead to a better understanding of a basic biological process underlying many conditions, from cancer to bacterial infection. In addition, we are developing a technique that may have value as a diagnostic tool.